@inproceedings{amine-romdhane-etal-2021-sifting,
    title = "Sifting {F}rench Tweets to Investigate the Impact of Covid-19 in Triggering Intense Anxiety",
    author = "Amine Romdhane, Mohamed  and
      Cabrio, Elena  and
      Villata, Serena",
    editor = "Denis, Pascal  and
      Grabar, Natalia  and
      Fraisse, Amel  and
      Cardon, R{\'e}mi  and
      Jacquemin, Bernard  and
      Kergosien, Eric  and
      Balvet, Antonio",
    booktitle = "Actes de la 28e Conf{\'e}rence sur le Traitement Automatique des Langues Naturelles. Volume 1 : conf{\'e}rence principale",
    month = "6",
    year = "2021",
    address = "Lille, France",
    publisher = "ATALA",
    url = "https://preview.aclanthology.org/ingest-emnlp/2021.jeptalnrecital-taln.21/",
    pages = "219--226",
    abstract = "Sifting French Tweets to Investigate the Impact of Covid-19 in Triggering Intense Anxiety. Social media can be leveraged to understand public sentiment and feelings in real-time, and target public health messages based on user interests and emotions. In this paper, we investigate the impact of the COVID-19 pandemic in triggering intense anxiety, relying on messages exchanged on Twitter. More specifically, we provide : i) a quantitative and qualitative analysis of a corpus of tweets in French related to coronavirus, and ii) a pipeline approach (a filtering mechanism followed by Neural Network methods) to satisfactory classify messages expressing intense anxiety on social media, considering the role played by emotions."
}